Questions tagged [doc2vec]
The doc2vec tag has no usage guidance.
19
questions
2
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2answers
117 views
classification of similar text input features with text output label
I hope somebody can provide guidance/input/advice on my project, where I believe AI can help.
I have a general understanding of AI, but I lack a formal training.
I've never built a neural net from ...
2
votes
0answers
16 views
Preprocessing for Document Similarity Using Doc2Vec
I'm trying to determine document similarity using Doc2Vec on a large series of legal opinions, which can contain some highly jargonistic language and phrases (e.g. en banc, de novo, etc.). I'm ...
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1answer
126 views
Embedding from Transformer-based model from paragraph or documnet (like Doc2Vec)
I have a set of data that contains the different lengths of sequences. On average the sequence length is 600. The dataset is like this:
...
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0answers
29 views
What is the meaning of, or explanation for, having multiple tags in a Doc2Vec model's TaggedDocuments?
I've tried reading the other answers on this topic but I'm unsure if I understand completely.
For my dataset, I have a series of tagged documents, "good" or "bad." Each document ...
2
votes
1answer
41 views
Word2Vec vs. Doc2Vec Word Vectors
I am doing some analysis on document similarity and was also interested in word similarity. I know that doc2vec inherits from word2vec and by default trains using word vectors which we can access.
My ...
1
vote
1answer
75 views
Clustering using both text and numerical features
I have a dataset that contains 2 types of features, one is generated from doc2vec and one is numerical feature. I would like to perform clustering analysis on them. However, due to the size of doc2vec ...
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0answers
33 views
doc2vec - paragraph or article as document
I'm trying to train a doc2vec model on the German wiki corpus. While looking for the best practice I've found different possibilities on how to create the training data.
Should I split every Wikipedia ...
0
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0answers
25 views
Building simple documents search engine
I'm having my first steps in the NLP and at the moment I'm looking forward to building my own documents search engine. I've already got to know with TFIDF in practical way and I've also read about ...
0
votes
1answer
22 views
Vector representation of documents for text classification
I'm looking for proper method of document embeddings. I know that doc2vec will give me the vector representations for given corpus, but how do I embed new documents? I need to train neural network ...
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0answers
15 views
Usage of Doc2Vec as feature extractor for text classification of websites with political articles
I have gathered political articles from polish websites for my engineering thesis. The main goal is to try to predict the website that input text belongs to. So for this few websites I want to create ...
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vote
1answer
64 views
DBSCAN on textual and numerical columns
I have a dataset which has two columns:
title price
sentence1 12
sentence2 13
I have used doc2vec to convert the ...
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0answers
28 views
Document Similarity to List of Words in Sentiment Analysis [closed]
How would you go about finding document similarity to a list of words in Sentiment Analysis?
Looking find document similarity to multiple lists of words in sentiment analysis. I had been working on ...
0
votes
2answers
296 views
Word2Vec with CNN
I am trying to classify documents using CNN (convolutional neural network) with Word2Vec embeddings. However to do this, it requires me to trim all texts to the same length. I just pad all the ...
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0answers
21 views
Topic alignment / topic modelling
What is the most efficient method for detecting whether the article is mostly about a specific topic, but without lots of data for training? My task is to determine how much a document is e.g. about ...
2
votes
1answer
146 views
How to implement LSTM using Doc2Vec vectors to get representation?
Hi all. I'm a newbie in ML. I read and found a paper about A Multi-Level Plagiarism Detection System Based on Deep Learning Algorithms and want to implement this model . But I can't find more about ...
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0answers
57 views
T-SNE good clustering but SVM classification poor
I am trying to classify in 4 different classes, paragraph embedding vector computed with doc2vec using an non-linear svm over them.
When I visualize the embeddings using tensorboard t-sne I can see ...
1
vote
1answer
2k views
Use embeddings to find similarity between documents
I need to find cosine similarity between two text documents. I need embeddings that reflect order of the word sequence, so I don't plan to use document vectors built with bag of words or TF/IDF. ...
2
votes
1answer
103 views
Approach to semantic similarity between documents
I was wondering what approach people would take, or point me in the right direction on this challenge I have set myself. I am pretty new at this, I have covered some area but want to expand my ...
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0answers
17 views
Can feature representation acquired by a same model but trained on different corpus be used on the same classification model?
For example, if I wanna do document classification with doc2vec embeddings, first I train the training set to get doc2vec embeddings, and fit the embeddings to a classification model; later on when I ...
